![]() We shall now build the package using CMake with the following flags cmake -DBLAS =open -DCUDNN_INCLUDE = $CUDA_HOME/include/ -DCUDNN_LIBRARY = $CUDA_HOME/lib64/libcudnn.so -DCMAKE_PREFIX_PATH = $CONDA_PREFIX -DCMAKE_INSTALL_PREFIX = $CONDA_PREFIX -DCMAKE_CXX_FLAGS = "-std=c++11". Within a build folder mkdir build & cd build We shall avoid polluting the caffe source tree by building Let’s clone caffe’s repo and its submodules into our home directory. Now let’s install the necessary dependencies in our current caffe environment: conda install lmdb openblas glog gflags hdf5 protobuf leveldb boost opencv cmake numpy =1.15 -y The virtual environment via: conda activate caffe You many of course use a different environment name, just be sure to adjustĪfter it prepares the environment and installs the default packages, activate ![]() Let’s create a virtual Conda environment called “caffe”: conda create -n caffe python =2.7 This guide is written for the following specs:įirst, get cuDNN by following this cuDNN Guide. Conda (see installation instructions here).The following guide shows you how to install install Caffe with CUDA
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